How to use the nmslib.saveIndex function in nmslib

if batch:
            num_threads = 10
            res = nmslib.knnQueryBatch(index, num_threads, k, query_matrix)
            for idx, v in enumerate(res):
                if idx < 5:
                    print(idx, v)
                if idx == 0:
                    for i in v:
                        print('q0', i, distance.cosine(q0, dataset[i,:]))
        else:
            for idx, data in enumerate(q):
                res = nmslib.knnQuery(index, k, data)
                if idx < 5:
                    print(idx, res)

    nmslib.saveIndex(index, index_name)

    print("The index %s is saved" % index_name)

    nmslib.freeIndex(index)

nmslib.createIndex(index, index_param)
    nmslib.setQueryTimeParams(index, query_time_param)

    print('Query time parameters are set')

    print("Results for the freshly created index:")

    k = 2
    if batch:
        num_threads = 10
        res = nmslib.knnQueryBatch(index, num_threads, k, QUERY_STRS)
    for idx, data in enumerate(QUERY_STRS):
        res = nmslib.knnQuery(index, k, data)
        print(idx, data, res, [DATA_STRS[i] for i in res])

    nmslib.saveIndex(index, index_name)

    print("The index %s is saved" % index_name)

    nmslib.freeIndex(index)

k = 3

    start = time.time()
    if fast:
        num_threads = 10
        query = read_data_fast('sample_queryset.txt')
        res = nmslib.knnQueryBatch(index, num_threads, k, query)
        for idx, v in enumerate(res):
            print(idx, v)
    else:
        for idx, data in enumerate(read_data('sample_queryset.txt')):
            print(idx, nmslib.knnQuery(index, k, data))
    end = time.time()
    print('querying done in %s secs' % (end - start))

    nmslib.saveIndex(index, index_name)

    print("The index %s is saved" % index_name)

    nmslib.freeIndex(index)

nmslib.createIndex(index, index_param)

    print('The index is created')

    nmslib.setQueryTimeParams(index,query_time_param)

    print('Query time parameters are set')

    print("Results for the freshly created index:")

    k = 3

    for idx, data in enumerate(read_sparse_data('sample_sparse_queryset.txt')):
        print(idx, nmslib.knnQuery(index, k, data))

    nmslib.saveIndex(index, index_name)

    print("The index %s is saved" % index_name)

    nmslib.freeIndex(index)

nmslib.createIndex(index, index_param)

    print('The index is created')

    nmslib.setQueryTimeParams(index,query_time_param)

    print('Query time parameters are set')

    print("Results for the freshly created index:")

    k = 3

    for idx, data in enumerate(read_data_as_string('sample_queryset.txt')):
        print(idx, nmslib.knnQuery(index, k, data))

    nmslib.saveIndex(index, index_name)

    print("The index %s is saved" % index_name)

    nmslib.freeIndex(index)

[],
            self._method_name,
            nmslib.DataType.DENSE_VECTOR,
            nmslib.DistType.FLOAT)

        for i, x in enumerate(X):
            nmslib.addDataPoint(self._index, i, x.tolist())

        if os.path.exists(self._index_name):
            logging.debug("Loading index from file")
            nmslib.loadIndex(self._index, self._index_name)
        else:
            logging.debug("Create Index")
            nmslib.createIndex(self._index, self._index_param)
            if self._save_index:
                nmslib.saveIndex(self._index, self._index_name)

        nmslib.setQueryTimeParams(self._index, self._query_param)